### Table 2. The number of closest pairs assigned to the same disk: stock.3d

"... In PAGE 5: ... This algorithm does not guarantee that two buckets closest to each other are always dis- tributed over different disks. However, results presented in the next section indicate that this happens rarely (see Table2 ). To complete the description of the algorithm, we need to specify a way to generate the edge weights.... In PAGE 6: ... Neither DM nor FX strictly dominates the other. Table2 tabulates the number of closest pairs of buckets that are mapped to the same disk by the different algorithms. It shows that this numberis rarely abovezerofor the minimax algorithm for the 120K records stock.... ..."

### Table 2. Distance between Centers (DC) and Sum of Radii (SR) of the closest pair of clusters with Chebyshev mo- ments

"... In PAGE 4: ...o order 2), ..., 55 moments (Upton order 9). The result for Legendre and Chebyshev moments are given in Table 1 and Table2 respectively for order of mo- ments a41a34a5a39a42a10a5 a130 a5 a180 a5a39a178a10a5a79a182a25a5 and a181 . It can be observed from table 1 that with Legendre mo- ments of order a40 and a41 clusters are disjoint if the standard deviation a1 a175 a9 of noise is a178 or less.... ..."

### Table 2. The number of closest pairs assigned to the same disk: DSMC.3d Declustering number of disks

1996

"... In PAGE 9: ... This algorithm does not guarantee that two buckets closest to each other are always distributed over different disks. However, results presented in the next section indicate that this happens rarely (See Table2 and Table 3). To complete the description of the algorithm, we need to specify a way to generate the edge weights.... ..."

Cited by 23

### Table 3. The number of closest pairs assigned to the same disk: stock.3d Declustering number of disks

1996

"... In PAGE 9: ... This algorithm does not guarantee that two buckets closest to each other are always distributed over different disks. However, results presented in the next section indicate that this happens rarely (See Table 2 and Table3 ). To complete the description of the algorithm, we need to specify a way to generate the edge weights.... ..."

Cited by 23

### Table 2. The number of closest pairs assigned to the same disk: DSMC.3d Declustering number of disks

1996

"... In PAGE 9: ... This algorithm does not guarantee that two buckets closest to each other are always distributed over different disks. However, results presented in the next section indicate that this happens rarely (See Table2 and Table 3). To complete the description of the algorithm, we need to specify a way to generate the edge weights.... ..."

Cited by 23

### Table 3. The number of closest pairs assigned to the same disk: stock.3d Declustering number of disks

1996

"... In PAGE 9: ... This algorithm does not guarantee that two buckets closest to each other are always distributed over different disks. However, results presented in the next section indicate that this happens rarely (See Table 2 and Table3 ). To complete the description of the algorithm, we need to specify a way to generate the edge weights.... ..."

Cited by 23

### Table 2. The number of closest pairs assigned to the same disk: stock.3d

1996

"... In PAGE 6: ... Neither DM nor FX strictly dominates the other. Table2 tabulates the number of closest pairs of buckets that are mapped to the same disk by the different algorithms. It shows that this numberis rarely abovezerofor the minimax algorithm for the 120K records stock.... ..."

Cited by 23

### Table 2. The number of closest pairs assigned to the same disk: stock.3d

1996

"... In PAGE 6: ... Neither DM nor FX strictly dominates the other. Table2 tabulates the number of closest pairs of buckets that are mapped to the same disk by the different algorithms. It shows that this numberis rarely abovezerofor the minimax algorithm for the 120K records stock.... ..."

Cited by 23

### Table 8: Closest Pair Given a set of line segments in the plane, the line intersection problem is the problem of determining all intersections of line segments in this set. For the rst four problems, algorithms running in O(n log(n)) time were implemented for the rst execu- tion. The second execution, using certi cation trails, runs in linear time. The rst execution algorithm used for line intersection runs in (O((k + n) log(n)) time where k is the number of intersections and n the num- ber of points. The second execution runs in O(k + n) time. Note that k may be quadratic in n.

1993

Cited by 4

### TABLE III PACKING IN COMPLEX PROJECTIVE SPACE: WE COMPARE OUR BEST CONFIGURATIONS (MB) OF K POINTS IN PT 1(C) AGAINST RANKIN BOUND. THE PACKING RADIUS OF AN ENSEMBLE IS MEASURED AS THE ACUTE ANGLE BETWEEN THE CLOSEST PAIR OF LINES.

in Non-coherent Communication in Multiple-Antenna Systems: Receiver design and Codebook construction